Child-Friendly Justice under the POCSO Act: A Critical Analysis of Implementation Barriers and Reform Imperatives
Bibliographic record
Abstract
The Protection of Children from Sexual Offences (POCSO) Act, 2012, represents India's legislative commitment to child-friendly justice, aiming to protect child survivors from secondary victimization during legal proceedings.This paper provides a critical analysis of the implementation of the child-friendly procedures under the act.This research uses a doctrinal methodology to examines statutes, case law, government reports, and scholarly commentary to evaluate the gap between the Act's progressive provisions and its practical application.The findings indicate that the Act's implementation is systemically undermined by three primary failures: significant infrastructural deficits, including the lack of truly child-friendly Special Courts; critical gaps in psycho-social support, particularly the ineffective provision of Support Persons; and procedural insensitivities from key stakeholders that result in the re-traumatization of the child.The study furthermore offers a comparative analysis with frameworks in the United Kingdom and Canada to identify international best practices.The paper concludes that without comprehensive reforms to address these institutional, infrastructural, and procedural failings, the child-friendly promise of the POCSO Act remains largely unrealised.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.038 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".